LLM Reference

OpenAI Privacy Filter

Released
2026-04-22
Last refreshed
2026-04-23
Status
Researched 45d ago
Open SourceCommercial use allowedLong contextClassification

OpenAI Privacy Filter has model metadata, but missing tracked provider pricing keeps it from being a default production pick.

Use it for

  • Teams evaluating long context and classification
  • Workloads that can use a 128k context window

Do not use it for

  • Cost-sensitive launches that need sourced token pricing
  • Vision or document-understanding workloads
  • Strict JSON or tool-calling flows
Specifications
Released
2026-04-22
Context
128k
Parameters
1.5B
Architecture
encoder_token_classifier
Specialization
safety
Openness
Open source
License
Apache 2.0(OSI)Commercial use allowed
Training
pretrained
Created by

Cutting-edge research and development.

San Francisco, California, United States
Founded 2015
Website
Pricing

No tracked provider token pricing is available yet.

About

OpenAI Privacy Filter is an Apache 2.0 open-weight bidirectional token-classification model for detecting and redacting personally identifiable information in text. OpenAI reports 1.5B total parameters, 50M active parameters, 128k-token context, and availability on Hugging Face and GitHub; this is a new specialist model release rather than a ChatGPT feature or endpoint alias.

OpenAI Privacy Filter is an open-source model. The structured metadata tracks a 128k-token context window. No headline benchmark score is tracked for OpenAI Privacy Filter yet.

Top use-case fit

Long context

Included by capability and metadata signals in the decision map.

Classification

Included by capability and metadata signals in the decision map.

Provider price ladder

No tracked provider token pricing is available for this model yet.

Capabilities

No model capability flags are currently sourced.

Benchmark peer barsfor Long context

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.